sensei

Automate skill frontmatter compliance improvement using the Ralph loop pattern.

Updated Mar 23, 2026

Search Tags:#token budget #ralph loop #skill compliance #compliance automation #frontmatter improvement

Ready to run

npx skills add https://github.com/chrishuffman5/skills --skill sensei-chrishuffman5

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: sensei
Source: https://github.com/chrishuffman5/skills/tree/main/sensei
Command: npx skills add https://github.com/chrishuffman5/skills --skill sensei-chrishuffman5

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires ralph-loop, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the improvement of skill frontmatter compliance using the Ralph loop pattern, ensuring skills reach Medium-High adherence with all tests passing.

Core Features & Use Cases

Compliance Evaluation: Iteratively evaluate and score skill frontmatter compliance against the agentskills.io spec.
Frontmatter Improvement: Add triggers, optimize descriptions, and validate references to enhance compliance.
Token Budget Analysis: Analyze token usage and suggest optimizations to stay within the recommended limit.
Batch Processing: Process multiple skills at once, improving adherence across your skill set.
Use Case: If you have a collection of skills that need compliance checks and improvements, Sensei can automate the process, saving you time and ensuring consistency.

Quick Start

Run the sensei skill on a single skill using: run sensei on <skill-name>.

Frequently Asked Questions about sensei

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate skill frontmatter compliance checks against the agentskills.io spec?▼

You can automate skill frontmatter compliance by running Sensei on a single skill using the command `run sensei on <skill-name>`, which iteratively evaluates and improves metadata until Medium-High adherence is reached.

What is the Ralph loop pattern for compliance automation?▼

The Ralph loop pattern drives compliance automation by iteratively evaluating frontmatter, applying improvements like adding triggers and optimizing descriptions, and validating references until all tests pass and Medium-High adherence is achieved.

How do I reduce token usage in skill metadata to stay within the recommended budget?▼

To reduce token usage, the skill analyzes token usage after compliance improvements are complete and prompts for action, suggesting optimizations to ensure skill metadata stays within the recommended token budget limit.

Do I need a Ralph loop implementation to check skill compliance?▼

Yes, Ralph loop implementation is required as a dependency to automate the iterative evaluation and frontmatter improvement process needed to achieve Medium-High skill compliance with passing tests.

Can I process multiple skills at once for frontmatter improvement?▼

Yes, batch processing allows you to improve frontmatter adherence across multiple skills at once, automating compliance checks and ensuring metadata consistency across your entire skill set.